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FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking
Cytoskeletal pattern formation and structural dynamics are key to a variety of biological functions and a detailed and quantitative analysis yields insight into finely tuned and well-balanced homeostasis and potential pathological alterations. High content life cell imaging of fluorescently labeled...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901806/ https://www.ncbi.nlm.nih.gov/pubmed/36745610 http://dx.doi.org/10.1371/journal.pone.0279336 |
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author | Hauke, Lara Primeßnig, Andreas Eltzner, Benjamin Radwitz, Jennifer Huckemann, Stefan F. Rehfeldt, Florian |
author_facet | Hauke, Lara Primeßnig, Andreas Eltzner, Benjamin Radwitz, Jennifer Huckemann, Stefan F. Rehfeldt, Florian |
author_sort | Hauke, Lara |
collection | PubMed |
description | Cytoskeletal pattern formation and structural dynamics are key to a variety of biological functions and a detailed and quantitative analysis yields insight into finely tuned and well-balanced homeostasis and potential pathological alterations. High content life cell imaging of fluorescently labeled cytoskeletal elements under physiological conditions is nowadays state-of-the-art and can record time lapse data for detailed experimental studies. However, systematic quantification of structures and in particular the dynamics (i.e. frame-to-frame tracking) are essential. Here, an unbiased, quantitative, and robust analysis workflow that can be highly automatized is needed. For this purpose we upgraded and expanded our fiber detection algorithm FilamentSensor (FS) to the FilamentSensor 2.0 (FS2.0) toolbox, allowing for automatic detection and segmentation of fibrous structures and the extraction of relevant data (center of mass, length, width, orientation, curvature) in real-time as well as tracking of these objects over time and cell event monitoring. |
format | Online Article Text |
id | pubmed-9901806 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-99018062023-02-07 FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking Hauke, Lara Primeßnig, Andreas Eltzner, Benjamin Radwitz, Jennifer Huckemann, Stefan F. Rehfeldt, Florian PLoS One Research Article Cytoskeletal pattern formation and structural dynamics are key to a variety of biological functions and a detailed and quantitative analysis yields insight into finely tuned and well-balanced homeostasis and potential pathological alterations. High content life cell imaging of fluorescently labeled cytoskeletal elements under physiological conditions is nowadays state-of-the-art and can record time lapse data for detailed experimental studies. However, systematic quantification of structures and in particular the dynamics (i.e. frame-to-frame tracking) are essential. Here, an unbiased, quantitative, and robust analysis workflow that can be highly automatized is needed. For this purpose we upgraded and expanded our fiber detection algorithm FilamentSensor (FS) to the FilamentSensor 2.0 (FS2.0) toolbox, allowing for automatic detection and segmentation of fibrous structures and the extraction of relevant data (center of mass, length, width, orientation, curvature) in real-time as well as tracking of these objects over time and cell event monitoring. Public Library of Science 2023-02-06 /pmc/articles/PMC9901806/ /pubmed/36745610 http://dx.doi.org/10.1371/journal.pone.0279336 Text en © 2023 Hauke et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Hauke, Lara Primeßnig, Andreas Eltzner, Benjamin Radwitz, Jennifer Huckemann, Stefan F. Rehfeldt, Florian FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking |
title | FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking |
title_full | FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking |
title_fullStr | FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking |
title_full_unstemmed | FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking |
title_short | FilamentSensor 2.0: An open-source modular toolbox for 2D/3D cytoskeletal filament tracking |
title_sort | filamentsensor 2.0: an open-source modular toolbox for 2d/3d cytoskeletal filament tracking |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9901806/ https://www.ncbi.nlm.nih.gov/pubmed/36745610 http://dx.doi.org/10.1371/journal.pone.0279336 |
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